Senior Planning & Analytics Manager

📋 Description

• • As a Senior Planning & Analytics Manager at Optro Inc., you will play a pivotal role in shaping the company’s go-to-market strategy by leveraging data to drive smarter, faster, and more profitable growth decisions. This role sits at the intersection of finance, sales, and operations, where your analytical rigor will directly influence how Optro allocates resources, sets quotas, designs territories, and identifies high-potential customer segments—ensuring every dollar invested delivers maximum return in a competitive SaaS landscape.
• • You will partner closely with commercial leadership to transform raw data into strategic foresight, enabling the company to anticipate market shifts, optimize sales performance, and scale efficiently. Your work will not only support quarterly planning cycles but also build the foundational analytics infrastructure that empowers sales leaders to make confident, data-backed decisions—turning insights into action and uncertainty into opportunity.
• • Optro is a high-growth, mission-driven SaaS leader trusted by over half of the Fortune 500 and seven of the Fortune 10 to manage audit, risk, ESG, and InfoSec challenges. With a culture rooted in customer obsession, gritty resilience, and collective win, you’ll join a team that values innovation, collaboration, and intellectual curiosity—where your contributions will be seen, heard, and amplified across the organization.
• • In this role, you will deepen your expertise in SaaS revenue operations, advanced financial modeling, and predictive analytics while gaining exposure to enterprise-scale GTM strategy. You’ll have the autonomy to design and implement scalable analytics frameworks, mentor cross-functional partners, and position yourself as a trusted advisor to senior leaders—building a legacy of impact that extends beyond spreadsheets into sustainable, measurable business outcomes.
• • Drive our go-to-market planning process to ensure we are investing in the right places at the right time by leading annual and quarterly planning cycles, aligning financial targets with sales capacity, and validating assumptions through scenario modeling and sensitivity analysis.
• • Understand SaaS sales models, different monetization approaches to measure bookings, revenue, capacity to help construct plan metrics, sales segmentation, territory assignment, and quota setting approaches—applying industry best practices to design equitable, motivating, and achievable compensation plans that drive desired behaviors.
• • Develop and maintain dashboards, scorecards, and KPI reports for sales, revenue, pricing, and customer performance using Tableau and Excel/GSheets, ensuring real-time visibility into pipeline health, win rates, deal velocity, and quota attainment across regions, products, and sales motions.
• • Standardize metrics across regions, channels, and product lines to create a single source of truth—eliminating inconsistencies in reporting, defining clear data governance standards, and establishing reusable templates that improve accuracy and reduce manual effort.
• • Analyze sales trends, customer behavior, product performance, and market dynamics to identify growth opportunities—conducting cohort analysis, win/loss reviews, and TAM/SAM/SOM modeling to uncover underserved segments, pricing inefficiencies, and expansion white spaces.
• • Translate complex data into clear, actionable insights and recommendations for commercial and sales leaders—crafting executive-ready presentations that distill technical findings into strategic narratives, supported by visualizations and risk-adjusted forecasts.
• • Establish go-to-market strategy, sales segmentation, KPI/scorecard framework—designing segmentation models based on firmographics, technographics, and buying behavior, then linking them to tailored sales plays, resource allocation, and performance tracking.
• • Create a dynamic propensity to buy / TAM model to help our sales team prioritize the customers and prospects who need our solutions—leveraging machine learning-ready features (even if using logistic regression or decision trees in Python/R) to score leads and accounts by likelihood to convert, lifetime value, and expansion potential.
• • Collaborate with passionate teammates across the company to execute key projects—partnering with Finance, Product, Marketing, and Customer Success to ensure alignment on goals, data definitions, and initiative timelines, fostering a culture of shared ownership and transparency.